Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add d-o-hub/github-template-ai-agents --skill learngit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/learn)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/learn"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/learn/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/learn"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00100 | $0.00828 |
| Opus 5.5 | $0.00040 | $0.00331 |
| Sonnet 5.5 | $0.00020 | $0.00166 |
| Haiku 4.5 | $0.00010 | $0.00083 |
Grade A, and why
learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn
Extract non-obvious session learnings into scoped AGENTS.md files to preserve knowledge across sessions.
When to Use
Activate after completing a non-trivial task to capture insights that would otherwise be lost.
Instructions
What to Capture (Non-Obvious Only)
- Hidden relationships between files or scripts not obvious from code.
- Execution paths that differ from what the code appears to do.
- Non-obvious config, env vars, or flags (see
agents-docs/ENVIRONMENT_VARIABLES.md). - Debugging breakthroughs where error messages were misleading.
- Files that must change together (e.g.,
AGENTS.md+agents-docs/AVAILABLE_SKILLS.mdwhen adding skills). - Build/test commands not documented in README.
- Architectural constraints discovered at runtime.
What NOT to Capture
- Obvious documentation or standard behavior.
- Duplicates of existing entries.
- Verbose explanations or session-specific notes.
Scoping Rules
Place learnings in the most specific file:
- Project-wide:
agents-docs/self-learning-rules.md(under## Recent Project-Wide Learnings). - Script-specific:
scripts/AGENTS.md. - Skill-specific:
.agents/skills/<name>/AGENTS.md.
Also write a fuller LESSON-NNN entry to agents-docs/LESSONS.md for archival.
Triple-Write Requirement
Every new non-obvious insight must be recorded in three places:
- Verbose Log: Add a full
LESSON-NNNentry toagents-docs/LESSONS.mdwith Issue/Root Cause/Solution. - Distilled Note (scoped): Add a 1–3 line note to the nearest
AGENTS.md(this is whatlearnautomates). - Distilled Note (project-wide): Add a 1–3 line note to
agents-docs/self-learning-rules.mdunder## Recent Project-Wide Learnings.
Format
- 1–3 lines per insight in
AGENTS.md. - Fits within
MAX_LINES_AGENTS_MD=200constraint. - Bulleted list under a "Learnings" or "Context" section.
See Also
agents-md— AGENTS.md best practicesskill-creator— Create and improve skills
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 85 lines · 100 tokens per session scan A fde8d015c970
learn is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 100 tokens to every session and 828 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
llm-wiki
Build and maintain an LLM-curated knowledge base from papers, articles, transcripts, notes and project findings. Ingest sources into linked Markdown, answer questions with citations, lint or upgrade a wiki, and preserve useful synthesis across sessions and agents. Also capture verified task experience, consolidate…
raytsystem-save
Stage a cited synthesis as a typed raytsystem DRAFT bundle and escaped preview. Use for SAVE, preserving a verified query answer, preparing a knowledge proposal, or creating a reviewable draft; never treat SAVE as canonical promotion or publication.
pkm-explore
Use when researching what the vault knows about a topic — performs graph + semantic exploration with gap analysis to map existing knowledge and find missing connections. Primarily used via the vault-explorer agent. Not for routine session-start context loading (hooks handle that).
orient
Use when user invokes /orient with a topic keyword, entity type, project name, time qualifier, or combination. Also triggers on "what do we know about X", "remind me about X", "where did we leave off on X". Provides targeted context loading — searches the MCP Memory Server graph, knowledge files, journal entries, and…
memory
Use when user invokes /memory with a subcommand (search, trace, add, episode, status). Also triggers on "search my memory for X", "add to memory", "what do I know about X" (when membrain is available), "memory status", "memory trace". Searches and manages the membrain knowledge graph via MCP tools or HTTP API.
capture
Use when user invokes /capture to capture information from the current conversation into a staging file for later reflection and knowledge graph processing. Accepts no arguments (auto-extract), specific facts as text, or filter keywords like "decisions" or "technical". Do NOT use when the user wants to write directly…